CSAMiningProcess: CSA Datamining Process

In STMotif: Discovery of Motifs in Spatial-Time Series

CSA Datamining Process

Description

Performs the complete Combined Series Approach (CSA) workflow: normalization with SAX encoding, motif discovery, and ranking. This is a convenience wrapper around NormSAX, SearchSTMotifs, and RankSTMotifs.

Usage

CSAMiningProcess(D, DS, w, a, sb, tb, si, ka)

Arguments

D	Dataset containing numeric values.
DS	Dataset containing SAX encoded values (recomputed internally; this parameter is kept for backward compatibility).
w	Word size (motif length in SAX symbols).
a	Number of letters in the SAX alphabet.
sb	Spatial block size (number of columns per block).
tb	Temporal block size (number of rows per block).
si	Minimum number of occurrences inside each block (sigma).
ka	Minimum number of spatial series with occurrences inside each block (kappa).

Value

A list of ranked motifs. Each motif contains:

isaxcode

Motif sequence in character format.

recmatrix

Matrix indicating which blocks contain this motif.

vecst

Data frame with columns s (spatial) and t (temporal) giving the start positions of the motif in the original dataset.

rank

List with ranking components: dist, word, qtd, proj.

Examples

D  <- STMotif::example_dataset
DS <- NormSAX(STMotif::example_dataset, 5)
rmotif <- CSAMiningProcess(D, DS, 4, 5, 4, 10, 2, 2)

STMotif documentation built on March 30, 2026, 1:06 a.m.